Explosives detection using optical spectroscopy

ABSTRACT

Detecting threat materials used in explosives is performed by receiving a sample, and selecting an area of interest on the sample suspected of containing a threat material indicative of an explosive. Detection also includes interrogating the area of interest with a Raman laser producing a Raman spectrum, and comparing an amplitude of a first spectral region in the Raman spectrum to a first predetermined threshold. Detection further includes performing a verification, if the determination indicates that the area of interest includes the threat material, by checking the interrogated area of interest for a secondary indicator of the presence of the threat material, by comparing an amplitude of a second spectral region in the Raman spectrum, which is different from the first spectral region in the Raman spectrum, to a second predetermined threshold, and activating an indicator if the verification indicates that the area of interest contains the threat material.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.15/292,253, filed Oct. 13, 2016, entitled “Explosive Detection UsingOptical Spectroscopy”, now allowed, which is a bypass continuation ofInternational Application No. PCT/US2015/026302, filed Apr. 17, 2015,entitled “EXPLOSIVES DETECTION USING OPTICAL SPECTROSCOPY”, which claimsthe benefit of U.S. Provisional Patent Application Ser. No. 61/980,636,filed Apr. 17, 2014, entitled “EXPLOSIVES DETECTION USING OPTICALSPECTROSCOPY”, the disclosures of which are hereby incorporated byreference.

BACKGROUND

Various aspects of the present invention relate generally to explosivesdetection and specifically to the use of optical spectroscopy to detectexplosives.

An improvised explosive device (IED) is a typically implemented as ahomemade bomb, which can be constructed and deployed differently thanconventional military means. For instance, in some cases, IEDs areconstructed from conventional, everyday objects including ammoniumnitrate fertilizers, steel pipes, pressure cookers, etc.

BRIEF SUMMARY

According to aspects of the present disclosure herein, a method fordetecting threat materials used in explosives is provided. The methodcomprises receiving a sample, and selecting an area of interest on thesample suspected of containing a threat material. The method alsocomprises interrogating the area of interest, with a Raman laser,thereby producing a Raman spectrum, and determining whether the area ofinterest includes the threat material by comparing an amplitude of afirst spectral region in the Raman spectrum, to a first predeterminedthreshold. The method still further comprises performing a verification,if the determination indicates that the area of interest includes thethreat material, by checking the interrogated area of interest for asecondary indicator of the presence of the threat material, where theverification is performed by comparing an amplitude of a second spectralregion in the Raman spectrum, which is different from the first spectralregion in the Raman spectrum, to a second predetermined threshold.Moreover, the method comprises activating an indicator if theverification indicates that the area of interest contains the threatmaterial.

According to further aspects of the present disclosure, the method onlyperforms the verification if the determination indicates that the areaof interest includes the threat material, e.g., if the amplitude of thefirst spectral region is greater than the first predetermined threshold.

Moreover, the method may comprise selecting the first spectral region,the second spectral region, or both, as a region that is sufficientlysmall to capture a single feature distinguishable from the measuredspectrum. For instance, where the threat material is a nitrate, themethod performs interrogation of the area of interest with the Ramanlaser to produce the Raman spectrum, wherein the Raman spectrum ismeasured in the first spectral region, which is set to a wave numbershift around 1050 cm⁻¹. In this manner, the method compares theamplitude of the measured portion of the Raman spectrum at approximately1050 cm⁻¹ to the predetermined threshold, where the predeterminedthreshold is set to a value indicative of a nitrate, as a nitrate isexpected to have a distinguishing feature in this area. Moreover, themethod performs the verification by checking for a feature at the secondspectral range (e.g., which is set to a wave number shift around 3225cm⁻¹ to detect ammonium nitrate as ammonium nitrate is expected to havea distinguishing feature in this area). As another example, the methodmay perform the verification by checking for a feature at a wave numbershift around 550 cm⁻¹ for urea nitrate as urea nitrate is expected tohave a distinguishing feature in this area.

According to further aspects of the present invention, a system fordetecting threat materials used in explosives, comprises a samplecollector, a sample stage, an interrogation station that includes aRaman laser source, a processor coupled to memory, and an output device.The sample collector collects a sample, and the sample stage receivesthe sample from the sample collector. The processor is furtherprogrammed to interact with the interrogation station to interrogate,with the Raman laser source, the area of interest thereby producing aRaman spectrum, and to determine whether the area of interest includesthe threat material by comparing an amplitude of a first spectral regionin the Raman spectrum, to a first predetermined threshold. The processoris further programmed to perform a verification, if the determinationindicates that the area of interest includes the threat material, bychecking the interrogated area of interest for a secondary indicator ofthe presence of the threat material, where the verification is performedby comparing an amplitude of a second spectral region in the Ramanspectrum, which is different from the first spectral region in the Ramanspectrum, to a second predetermined threshold. Moreover, the processoris programmed to activate an indicator if the verification indicatesthat the sample contains the threat material.

BRIEF DESCRIPTION OF THE SEVERAL VIEWS OF THE DRAWINGS

FIG. 1 is a block diagram of an illustrative system detecting explosivesusing optical spectroscopy, according to various aspects of the presentdisclosure;

FIG. 2 is a flow chart illustrating a method for detecting explosivesusing optical spectroscopy, according to various aspects of the presentdisclosure;

FIG. 3 is a graph illustrating Raman spectra for three phases ofammonium nitrate from 200 to 1100 cm⁻¹, according to various aspects ofthe present disclosure; and

FIG. 4 is a graph illustrating Raman spectra for three phases ofammonium nitrate from 200 to 3500 cm⁻¹, according to various aspects ofthe present disclosure.

DETAILED DESCRIPTION

Various aspects of the present disclosure provide systems and methodsfor detecting, characterizing, or both detecting and characterizing,threat materials such as explosives using optical spectroscopy. Some ofthe systems are portable to bring on-site to detect explosives beforethe explosives have a chance to vaporize. Further, the systems andmethods can detect the explosive in particulate form, which reducesreliance on dissolved or reacted materials that may give a falsepositives with common environmental salts that also include explosivebase materials (e.g., ammonium nitrates, urea nitrates, etc.). Theexplosive may be detected from an unexploded state or a post-blast(i.e., exploded) state. Further analysis can be performed on theexplosive to determine the source of the explosive, including theprocess and materials used to make the explosive. In this regard,systems and methods are provided, which are capable of detectingexplosives, including homemade explosives, without the requirement toperturb the native state of the explosives.

System Overview:

Referring now to the drawings, and in particular to FIG. 1, a system 100for detecting explosives using optical spectroscopy is illustrated,according to various aspects of the present disclosure. The system 100includes in general, a sample collector 102 that provides a sample thatmay contain a threat material, such as may be found in explosives. Thesample collected by the sample collector 102 is positioned for analysison a sample stage 104 for interrogation by one or more interrogationdevices of an interrogation station 106. Interrogation devices includefor instance, a Raman spectrometer fluorescence system, imaging cameraand microscope, combinations thereof, etc. In some embodiments, aprocessor 108 is used to control the sample collector 102, the samplestage 104, one or more of the interrogation device(s) of theinterrogation station 106, combinations of the above, etc.

Further, the processor 108 can access an output device 112 such as anindicator used to sound an alarm, to report out the results of a sampleanalysis, etc. The output device 112 can also include a screen,printout, transmission device (cellular, network, etc.) or othersuitable device, to convey information, including measurements, analysisresults, an analysis of a detected explosive, an indication of thesource of the explosive, or combination thereof. A determination of thesource of the explosive can include the process used to make thedetected explosive and/or materials used to make the explosive.

In this regard, the processor 108 interacts with memory 110 to storethreshold variables, control instructions, set points, interrogationcontrol parameters, evaluation algorithms, any other necessaryinformation to perform explosives detection, etc., as set out herein.Moreover, the memory 110 can be used by the processor 108 to storemeasurements, evaluation data, evaluation results, or other informationthat is generated during use. Further, by coupling the processor 110 tothe memory 110, the processor 108 is programmed to interact with thesample collector 102, sample stage 104, interrogation station 106,output device(s) 112, or combinations thereof, to implement thefunctions set out in greater detail herein, including the method 200 ofFIG. 2, discussed herein.

In use, a sample is received (e.g., from the sample collector 102, whichmay be integral to the remainder of the system 100, or implemented as aseparate component). In an illustrative example, the sample is receivedonto the sample stage 104, such as a multi-axis motorized stage that iscontrolled by the processor 108 to move the sample relative to the stagein the X dimension, Y dimension, Z dimension, or combination thereof, toevaluate the collected sample. For instance, depending upon thecollected sample, the sample area may be as large as 2 millimeters×2millimeters. However, a particulate that is a threat material may beapproximately 1-2 microns or less. As such, the sample stage 104 may bea motorized stage having a high degree of accuracy (e.g., to aresolution of 0.1 microns).

According to an illustrative example of the present disclosure,interrogation device(s) may be implemented within, or otherwisecoordinated with the optical interrogation station 106. In someembodiments, a first interrogation device is implemented as a firstoptical device that includes a first illumination source 106A (e.g., aXenon arc source), which directs a first light beam through anyappropriate lenses, filters, or other optical devices 106B, and throughan optional element 106C such as an objective lens, towards the sample.In this regard, the sample has been advanced to a sample substratereceiving area 104A of the sample stage 104. Light from the surface ofsample is reflected and is focused onto a camera 106D to form an imageof the sample. This image comprises first data that is processed by theprocessor 108, and which may be used to determine one or more targetlocations and/or fields of view, which may be of interest for furtherinterrogation. Here, the target locations (i.e., areas of interest) aredetected by the processor 108 (e.g., using techniques such as detectingfluorescence, bright field image processing or dark field imageprocessing, as will be described in greater detail herein).

The processor 108 thus selects a target location (area of interest onthe sample), which is suspected of containing a threat material, andinterrogates that targeted location. For instance, in some embodiments,a second interrogation device is implemented as a second optical device106E that provides a beam from a suitable laser source, which passesthrough any appropriate lenses, filters, or other optional opticaldevices 104F, and is optionally focused by an element 106G, e.g., anobjective lens, onto the sample. For instance, the beam from the secondoptical device 106E is directed at the specific areas of interest thatare specified from the target locations identified by the processor 108,e.g., based upon an analysis of the first data. The second beam isreflected from the sample, where the second beam is directed to aspectrometer 106H, such as a Raman spectrometer. The interrogation datafrom the second optical device 106E (e.g., a targeted vibrationalanalysis produced by Raman spectroscopy that is recorded by thespectrometer 106H) is used to identify whether the targeted area ofinterest includes a threat material such as an ingredient of anexplosive, such as a nitrate, as will be described in greater detailherein.

The specific components described above with reference to theinterrogation station 106 are discussed and schematically illustrated asseparate components for clarity of discussion. However, in practice,components that make up the interrogation device(s) may be independentor shared. Likewise, there may be a single interrogation device ormultiple interrogation devices, so long as the described functions(e.g., targeting and targeted interrogation) are capable of beingperformed.

The processor 108 determines whether the area of interest includes thethreat material by comparing an amplitude of a first spectral regionmeasured during the interrogation, to a first predetermined threshold.In FIG. 1, the first spectral region is illustrated in block diagramform, as being extracted by a first spectral range filter 114. The firstspectral range filter can be an optical filter (e.g., a narrow bandpassfilter) or the first spectral range filter 114 can be implementeddigitally by the processor 108. The first threshold is extracted fromthe memory 110 for the comparison. If (and only if) the determinationindicates that the area of interest includes the threat material, thesystem performs a verification. The verification is performed bycomparing an amplitude of a second spectral region different from thefirst spectral region, measured during the interrogation, to a secondpredetermined threshold. In FIG. 1, the second spectral region isillustrated in block diagram form, as being extracted by a secondspectral range filter 116. The second spectral range filter can be anoptical filter (e.g., a narrow bandpass filter) or the second spectralrange filter 116 can be implemented digitally by the processor 108.

The processor 108 activates the output device 112 if the verificationindicates that the sample contains the threat material. In this regard,the processor 108 interacts with the indicator 112 to communicate theresults of the analysis to a user. Moreover, the processor 108discriminates between specific threat material(s) of interest(determined by detection and verification) and other particulates thathave been collected.

Method of Detecting a Threat Material:

Referring to FIG. 2, a method 200 for detecting explosives (includingexplosive precursors and post-blast products) using optical spectroscopyis shown. The method 200 may be implemented, for instance, on the system100 of FIG. 1.

The method 200 includes receiving at 202, a sample. The sample may bereceived at 202, in any applicable way.

Collection:

In exemplary implementations, the sample collector 102 of FIG. 1 can beused to collect a sample, which is received by the method 200. Forinstance, a sample collector can be implemented as a collection systemthat is configured to collect a sample onto a sample substrate (e.g., anon-Raman active membrane filter material or other form of filtermaterial). The collection device may comprise, for example, a collector,solid surface small area impactor, electrostatic precipitation device,cyclone device, or other collection technology.

In an illustrative example, the collection device draws and acceleratesa fluid stream, such as from the ambient air, through the collector.Particulate matter that is entrained in the stream is extracted anddeposited onto a sample substrate (e.g., the filter) in a relativelysmall, defined sample area. The filter may be manually placed in thecollection system or the filter may be automatically placed in thecollection system (e.g., via a translation subsystem).

Examples of a suitable collection device to create the sample aredisclosed in U.S. Pat. No. 7,499,167, entitled “AEROSOL TRIGGER DEVICEAND METHODS OF DETECTING PARTICULATES OF INTEREST USING AN AEROSOLTRIGGER DEVICE” filed Jul. 14, 2006 by Rodney S. Black et al., and inU.S. Pat. No. 7,993,585 entitled “BIOLOGICAL AND CHEMICAL MONITORING”filed on Jul. 14, 2006 by Rodney S. Black et al., the disclosures ofwhich are hereby incorporated by reference in their entirety.

For instance, the collection device may include a pre-impactor to filterparticulates in the fluid stream to a generally predetermined size. Asfurther examples, the collector may be implemented by a device thatexhibits high efficiency, low pressure differential particulatecollection, aerodynamic particle size filtration, and which can provideuniform coverage of a planar and flat surface with particulate matter.Thus, the collection system can provide homogeneous spatial distributionof particulate matter onto a sample substrate.

As mentioned above, the sample may be created by impacting a fluidstream onto a substrate. Any type of substrate may be used including analuminum substrate. However, it has been found through experimentationthat a gold substrate (plated or solid) may be preferred, because thegold substrate preserves the sample longer than an aluminum substrate,especially when the sample includes ammonium nitrate. For instance, theammonium nitrate may chemically react with the aluminum, leading to amore rapid loss of the sample than on a gold substrate.

Another example of receiving a sample is to receive a sample that waspreviously collected, placed, or otherwise presented on a substrate.

The sample may be enclosed in a relatively small container to preventevaporative loss of small particles of explosive. For example, thesample may include ammonium nitrate. However, when ammonium nitratedissociates, the result is ammonia and nitric acid; both of which arevolatile. If these ammonia and nitric acid molecules are lost to theatmosphere, the rate of sample loss to evaporation is higher than wouldbe expected from just the vapor pressure of ammonium nitrate. Becausethe ammonia and nitric acid molecules are continually lost, noequilibrium is established and the ammonium nitrate continuallydissociates. Thus, to preserve the sample, it may be desirable tocontain the sample inside a relatively small, enclosed container.

On the other hand, the sample may be in an open environment or otherwisenot contained in an enclosed container after impacting the substrate.For instance, the sample may be received onto a sample substrate in anopen environment, e.g., through impaction by a collector describedherein, which can be implemented as part of an integral or otherwiseautomated optical system, e.g., as described with reference to FIG. 1.Such a system allows the sample to be processed on-site or relativelyquickly after collection.

Evaluation:

The method 200 also comprises selecting, at 204, an area of interest onthe sample, which is suspected of containing a threat material. Forexample, the sample may be affected with a fluorescent marker or acontrast dye. A fluorescent optical device (e.g., deep ultravioletexcitation device) may illuminate the sample, and the areas thatfluoresce may be selected as areas of interest. As yet an additionalexample, a first optical device can use spectral “fingerprints” toclassify, identify and/or distinguish sample regions or specificparticulates within sample regions for additional targetedinterrogation. Selective spectral regions may contain strong scatteringfeatures that are indicative of a class of particles. In this wayspectral regions can be used in a manner similar to fluorescenceemission as a discrimination tool. As another example, the location ofparticulates formed in the sample may be affected by the particulatesize, e.g., particulate size may decrease with the distance within thesample from the center of the nozzle of the collector. This informationmay be utilized, for example, when selecting target locations based, atleast in part, upon particulates of a predetermined size range.

Moreover, darkfield, lightfield, and other optical processing techniquescan be used to identify particulates that may be of interest. On theother hand, the area of interest may be selected with a raster scan ofthe sample, where the entire sample is eventually interrogated. Theselected area for targeted evaluation may be down to a single particlesize. In this regard, various techniques above can be combined in anydesired combination. For instance, a bright field image can be comparedto a fluorescence image, etc. Another exemplary technique comprises theuse of images, e.g., from a camera for the selection of specific sizesand/or shapes of target particulates. Targeting a particular size rangeby image processing may thus increase the likelihood of identifyingparticulates that may be of interest. Using corresponding imageprocessing techniques, particles of a specific size range and/or shapecan be located in the field of view for interrogation. Still further,discrimination techniques can be used to “rule out” areas as being ofinterest.

As such, the presence of various matrix (sand, dust, lint) andinterferent materials does not affect the detection accuracy. Theselection of the area (or areas) of interest may be carried out, forinstance, by one or more of the interrogation device(s) of theinterrogation station 106 and the processor 108 of FIG. 1.

The process at 204 may thus be utilized to segregate innocuous materialsfrom targeted materials. Notably, a sample collection area may be on theorder of 1 millimeters (mm) to 2 mm squared. However, a particle ofinterest may be on the order of 1 micron or smaller. As such, thesegregation of innocuous material significantly speeds up the evaluationprocess.

The method 200 also comprises interrogating, at 206, with an opticalsource, the area of interest. For example, a Raman laser may be used tointerrogate the area of interest to produce a Raman spectrum of aportion of the area of interest. Another example is usinginterferometric spectroscopy to interrogate at least a portion of thearea of interest to produce a spectrum of the portion of the area ofinterest. For instance, the interrogation at 206 may be carried out by alaser and Raman spectrometer of the interrogation station 106, and theprocessor 108 of FIG. 1.

The method 200 also includes determining, at 208, whether the area ofinterest includes the threat material by comparing an amplitude of afirst spectral region measured during the interrogation, to a firstpredetermined threshold. For instance, a first portion of a spectrum (orseries of spectra) is compared to a first predetermined threshold todetermine if the sample includes a component of a threat material (e.g.,an explosive including a nitrate). The determination may be performed,for instance, by the interrogation station 106, processor 108, memory110, and first spectral range filter 114 of FIG. 1.

By way of example, when using Raman spectroscopy, the amplitude of thespectrum at approximately 1050 cm⁻¹ will be greater than the surroundingspectrum values if a nitrate is present. That is, the spectrum exhibitsa spike at around 1050 cm⁻¹. Therefore, if the amplitude of the spectrumat 1050 cm⁻¹ of the Raman spectrum is above a certain level (thepredetermined first threshold level), then the sample may be said toinclude a nitrate. Thus, in an example implementation, the method 200comprises interrogating at least a portion of the area of interest witha Raman laser to produce a Raman spectrum, wherein the Raman spectrum ismeasured in the first spectral region, which is set to a wave numbershift around 1050 cm⁻¹. As such, the method 200 may also comprisecomparing the amplitude of the measured portion of the Raman spectrum atapproximately 1050 cm⁻¹ to the predetermined threshold, where thepredetermined threshold is set to a value corresponding to a feature inthe first spectral range that is indicative of a nitrate.

Notably, here, the first spectral region can be selected as a narrowregion, e.g., a region that is sufficiently small to capture a singlefeature of the captured spectrum, such as the spike around 1050 cm⁻¹that is indicative of a nitrate. In practice, other threat materialswill likely have a defining feature in a different wavenumber shift. Assuch, the first spectral range is selected as a range large enough tocapture the feature or features in the Raman spectrum that are ofinterest. However, the tighter the filter (i.e., the smaller thespectral range), the less computationally intensive, and hence, thefaster the initial evaluation is. For instance, in an exampleimplementation, the method uses a first spectral range filter, e.g., afixed narrow bandpass filter that filters the spectrum from the sampleto an isolated, narrow spectral range, e.g., potentially as narrow as toa specific wave number shift, such as around 1050 cm⁻¹. Correspondingly,the method at 206, evaluates spectral information solely within thenarrow spectral range, e.g., by the processor 108 of FIG. 1. Thisapproach minimizes the amount of data that must be analyzed. Also, thisapproach eliminates the complexity of an adjustable or otherwise tunablefilter. Moreover, this approach eliminates the processing delaysinherent in controlling a tunable or otherwise adjustable filter, whichmay take too long to adjust given the volatility of the sample tovaporize or dissociate, especially when evaluating a post-blastenvironment.

If no nitrate is found, the method 200 may loop to 204 to select anotherarea of interest on the sample or the method 200 may end. If the method200 ends without detecting a threat material at all, then the method 200may end at 210 without activating an indicator that indicates that anexplosive is found.

However, if a threat material (e.g., a nitrate) is found (i.e., if thedetermination indicates that the area of interest includes the threatmaterial), then the method 200 performs a verification. Thus, the method200 may only perform the verification if the amplitude of the firstspectral region is greater than the first predetermined threshold.

More particularly, the method 200 comprises performing, at 212, averification by checking for a secondary indicator of the presence ofthe threat material, where the verification is performed by comparing anamplitude of a second spectral region different from the first spectralregion, measured during the interrogation, to a second predeterminedthreshold. The verification may be performed, for instance, by theinterrogation station 106, processor 108, memory 110, and secondspectral range filter 116 of FIG. 1.

In an example implementation, at 212, a second portion of a spectrum (orseries of spectra) is compared to a second predetermined threshold todetermine if the sample includes a secondary indicator of an explosive.In other words, once the method 200 has determined the presence of athreat material (e.g., a nitrate) in the sample, the method 200 looksfor other secondary indicators of an explosive (e.g., ammonia forammonium nitrate, urea for urea nitrate, etc.).

For example, when using Raman spectroscopy, the amplitude of thespectrum at approximately 3225 cm⁻¹ will be greater if ammonia ispresent or approximately 550 cm⁻¹ will be greater if urea is present.

More particularly, the method 200 may perform the verification byinterrogating at least a portion of the area of interest with a Ramanlaser to produce a Raman spectrum, wherein the Raman spectrum ismeasured in the second spectral region, which is set to a wave numbershift around 3225 cm⁻¹, and determining if the sample includes ammoniumnitrate by comparing the amplitude of the measured portion of the Ramanspectrum at approximately 3225 cm⁻¹ to the predetermined threshold,where the second threshold is set to a value corresponding to a featurein the second spectral range indicative of ammonium nitrate.

Similarly, the method 200 may perform the verification by interrogatingat least a portion of the area of interest with a Raman laser to producea Raman spectrum, wherein the Raman spectrum is measured in the secondspectral region, which is set to a wave number shift around 550 cm⁻¹ anddetermining if the sample includes urea nitrate by comparing theamplitude of the measured portion of the Raman spectrum at approximately550 cm⁻¹ to the predetermined threshold, where the second threshold isset to a value corresponding to a feature in the second spectral rangeindicative of urea nitrate.

If no secondary indicator of an explosive is present, then the method200 may loop back to select a new area of interest or end. However, if asecondary indicator is detected, then at 214, an indicator is activatedto signal that an explosive is present in the sample. The indicator maybe any appropriate signal such as a light, a buzzer, a printout, adisplay (e.g., a monitor, LED display, LCD display, etc.), an e-mail, atext message, etc.

The method may ultimately continue with additional analysis, such asstoring information while the collection system continues to collectsamples that are analyzed to develop trends. Moreover, once a materialis determined to be a threat material, more detailed analysis can becarried out. For instance, signatures can be utilized to identify thematerial with specificity. Samples can be continuously collected toestimate concentration, etc. For instance, the processor 108 can comparethe collected spectra (e.g., a more complete version of the spectrumthan used at 208 and 212) to signatures stored in the memory 110 toidentify the specific nature of the threat material. The signatures canalso be used to provide insight into identifying the process andmaterials used to make the explosive, such as by combining the resultsof the signature analysis with domain knowledge programmed into thememory 110 of FIG. 1.

Spectroscopy

To perform the interrogation at 206, a spectrometer may be used. Inillustrative examples, a high throughput spectrometer may be utilized toevaluate the sample (e.g., using 10⁶ off-axis diffuse light rejection,optimized Etendue for scattering collection optics, etc.). The systemshould be capable of spatial and spectral separation. However, spatialseparation may not be necessary, such as if laser scanning is used. Inillustrative implementations, the spectrometer is polarizationdispersion invariant, and capable of broad spectral coverage and highspectral resolution to improve target identification.

Moreover, the system may utilize an interferometric method that reducessystem requirements by removing the grating dispersion element (e.g.,removing the need of a 2-D detector). However, a thermoelectric-cooledlinear array of finite elements may be utilized as the detector.

Further, the spectrometer may utilize a high collection angle, narrowdepth-of-field system, coupled with fully automated image collection andprocessing, followed by automated targeting of selected particles (e.g.,starting at 204 of the method 200), thus facilitating the ability toquickly analyze particles as small as 300 nm diameter.

Observations:

The method 200 implements a two-determination process in evaluating aspectrum to determine a presence of an explosive in a sample. In thefirst determination (e.g., 208), the spectrum is checked only around acertain range to determine a presence of an indicator of an explosive(e.g., a feature in the spectrum that is indicative of a nitrate). Forexample, in a Raman spectrum collected from the sample, a narrow rangearound 1050 cm⁻¹ may be checked for the presence of a nitrate. All otherportions of the spectrum may be ignored during this first determination.If (and thus only after) a nitrate is found, the second determinationchecks for a secondary indicator of an explosive. Again, the spectrum ischecked only around the ranges of the secondary indicators (e.g., ˜3225cm⁻¹ for a feature indicative of ammonia, ˜550 cm⁻¹ for a featureindicative of urea, etc.). For example, to determine if a sampleincludes ammonium nitrate using Raman spectroscopy, the Raman spectrumof the sample need only be compared at approximately 1050 cm⁻¹ and 3225cm⁻¹.

Further, more than one spectrum may be created. For example, thespectrum used in the first determination may be created using a Ramanlaser, and the spectrum used in the second determination may be createdusing interferometric spectroscopy. As another example, the spectrumused in the first determination may be created using a Raman laser of afirst wavelength, and the spectrum used in the second determination maybe created using a Raman laser of a second wavelength. Differentexcitation lasers on the same sample may produce different spectra toaid in determining if a sample includes an explosive.

Thus, the explosive detection process according to the method 200 as setout herein, provides faster computation times for processing an entiresample over methods that require the entire sample spectra to becompared to known Raman signatures to determine a presence of anexplosive.

Turning now to FIGS. 3-4, Raman spectra of three phases of ammoniumnitrate are shown. In FIG. 3, the bottom spectrum 302 shows ammoniumnitrate in phase II, the middle spectrum 304 shows ammonium nitrate inphase III, and the top spectrum 306 shows ammonium nitrate in phase IV.Similarly, in FIG. 4, the bottom spectrum 402 shows ammonium nitrate inphase II, the middle spectrum 404 shows ammonium nitrate in phase III,and the top spectrum 406 shows ammonium nitrate in phase IV.

The method 200 of FIG. 2 can use this information to help determine asource of ammonium nitrate found in a sample. For instance, despite thedifferent spectra, each phase of ammonium nitrate exhibits a featureidentified by a strong peak at approximately 1050 cm⁻¹. As such, anarrow filtered scan in this region can accurately and quicklydistinguish each sample as a nitrate.

Crystal Phase Distribution:

Ammonium nitrate exhibits polymorphism and has six stable crystallinephases. Raman spectra distinguish between crystalline phases because thecrystalline arrangement determines which vibrations are excited (andtherefore observed) and produces shifts in the vibrational energy ofsome bonds.

Under normal laboratory conditions (approximately 293 K), phase IV isexpected to be the dominant phase of ammonium nitrate. However, this isnot always the case, because the phase of ammonium nitrate is alsodependent on a preparation method. For example, if ammonium nitrate isdissolved and then rapidly dried to generate microscopic crystals, theremay be indications of both phases II and III, and these phases canpersist for days. Thus, if an explosive is detected in a sample, thenthe Raman spectra can be compared to the signatures to determine thephase of the explosive, which is indicative of the preparation processof the explosive. That is, field samples may also contain a distributionof crystal phases that is indicative of the ammonium nitrate preparationmethod, thus providing a forensic tool.

Another method of creating ammonium nitrate can be grinding prills ofmanufactured calcium ammonium nitrate. Moreover, the storage temperatureof the ammonium nitrate may affect the dominant phases of the ammoniumnitrate detected in the sample. Therefore, through looking at the phasesof the ammonium nitrate in the sample, a storage temperature,manufacturing process, or both may be discovered to help identify thesource of the explosive.

Although ammonium nitrate is discussed here, the source of anyapplicable explosive (including explosive precursors and post-blastproducts) may be found. For instance, the system 100 of FIG. 1 can betuned to a desired product or products of interest. As mentioned above,the devices disclosed in U.S. Pat. No. 7,993,585 can be modified tosupport the system 100 and/or method 200 described herein. As such, inillustrative implementations, explosives, explosive precursors, andpost-blast products can be identified using particulate matter down to apicogram in mass or less than 500 nanometers in size.

Sample Persistence:

Conventionally prepared samples of ammonium nitrate may, under somecollection and storage conditions, be lost to sublimation, evaporationor chemical reactions within hours or days. However, the system hereincan be used to observe particles over time and monitor their loss ratesor reaction products. When ammonium nitrate dissociates, it formsammonia and nitric acid:NH₄NO₃→NH₃+HNO₃

Both of these reaction products are volatile. If these molecules arelost to the atmosphere, the rate of sample loss to evaporation is higherthan would be expected from the vapor pressure of ammonium nitrate.Because the products are continually lost, no equilibrium is establishedand the reaction continues to be driven towards the products. Inaddition to this dissociation and evaporation loss mechanism, it is alsopossible to lose ammonium nitrate through other chemical reactions. Forinstance, as noted above, ammonium nitrate placed on an aluminumsubstrate is lost more rapidly than ammonium nitrate placed on a goldsubstrate.

Miscellaneous:

Aspects of the present invention herein provide a system that canexamine trace quantities of particulate matter down to a picogram inmass/half a micrometer in size. That is, the system described herein isable to identify threat materials based on examining a single,microscopic particle of the target explosive. The evaluation is carriedout using microscopy optics, highly sensitive detectors, and patternrecognition software that allows the process from sample collectionthrough identification to be fully automated. As noted in greater detailherein, the system can report the chemical makeup of the sample.Further, as noted in greater detail herein, the system can be programmedto automatically synthesize all of the data and provide information onthe likely sample origin. By way of example, there may be forensicinformation in examining the distribution of the crystalline structureof ammonium nitrate samples. For instance, the crystal structure dependson the material preparation process. As such, examining the crystalstructure can reveal information about the source of the ammoniumnitrate used in a homemade explosive or other device.

Moreover, Raman signatures as disclosed herein, which allow for theidentification of a wide range of chemical compounds, includingexplosives, their synthesis precursors, and post-blast products.

The system herein has the unique capability of detecting the intactammonium nitrate and urea nitrate crystals without depending ondetecting the dissolved or reacted material. This enables the system toreadily distinguish target materials from common environmental saltsthat also contain ammonium, urea, or nitrate ions.

Conventional methods of explosives detection can dissolve condensedphase materials and often obfuscate the findings. More generally,conventional methods of explosives detection are ineffective at dealingwith the problematic sample degradation properties of explosivematerials.

To the contrary, according to aspects of the present disclosure, anexplosives detection system and method are provided, which are highlyreliable, and which provide high true positive and low false positiverates. The reliability is predicated at least in part, upon a firstfocused evaluation of for a specific explosive component (e.g., anitrate) and then by independently collaborating the suggestion of thepresence of an explosive by performing a second focused evaluation bydetecting a secondary indicator of an explosive, such as a portion of aspectrum that is outside the bandwidth evaluated in the first focusedevaluation. By properly setting the thresholds that are used to judgethe presence of a signal at the focused evaluation range, a highconfidence of true positive and low false positive rates is realized.

Moreover, because of the speed and capability of the system,implementations are available that can perform a detection beforematerials vaporize, thus creating the opportunity for collecting andpreserving forensic evidence. In this regard, materials can be evaluatedin particulate form.

Aspects of the present invention combine Raman spectroscopy, microscopicimaging, and software automation to analyze trace (≥1 picogram)materials. The systems can determine chemical composition, quantifyparticle size, characterize crystalline phase, etc. Moreover, thesystems herein can be engineered or otherwise configured for specificmissions (e.g., by specifying specific targets to evaluate, and/or bysetting custom thresholds for those selected targets). Still further,the system can be constructed in a manner that is one-person portable(e.g., about 1.5 cubic feet), and which provide fully automated sampleanalysis utilizing optical analysis with no consumables.

Trace samples can diminish due to evaporation and chemical reactions. Inthis manner, the systems and methods herein can be used to monitor therate of loss and reaction products of collected samples. The collectedinformation can be used to provide recommendations for minimizing sampleloss. The systems herein may also be configured to measure the crystalphase in sample, and determine its potential value as a forensicsignature.

Aspects of the present invention are described herein with reference toflowchart illustrations and/or block diagrams of methods, apparatus(systems) and computer program products according to embodiments of theinvention. It will be understood that each block of the flowchartillustrations and/or block diagrams, and combinations of blocks in theflowchart illustrations and/or block diagrams, can be implemented bycomputer program instructions. These computer program instructions maybe written in any combination of one or more programming languages, andmay be provided to a processor of a general purpose computer, specialpurpose computer, or other programmable data processing apparatus toproduce a machine, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, create means for implementing the functions/acts specified inthe flowchart and/or block diagram block or blocks.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the invention. Asused herein, the singular forms “a,” “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise. It will be further understood that the terms “comprises”and/or “comprising,” when used in this specification, specify thepresence of stated features, integers, steps, operations, elements,and/or components, but do not preclude the presence or addition of oneor more other features, integers, steps, operations, elements,components, and/or groups thereof.

The corresponding structures, materials, acts, and equivalents of allmeans or step plus function elements in the claims below are intended toinclude any structure, material, or act for performing the function incombination with other claimed elements as specifically claimed. Thedescription of the present invention has been presented for purposes ofillustration and description, but is not intended to be exhaustive orlimited to the invention in the form disclosed. Many modifications andvariations will be apparent to those of ordinary skill in the artwithout departing from the scope and spirit of the invention. Aspects ofthe invention were chosen and described in order to best explain theprinciples of the invention and the practical application, and to enableothers of ordinary skill in the art to understand the invention forvarious embodiments with various modifications as are suited to theparticular use contemplated.

What is claimed is:
 1. A method for detecting threat materials used inexplosives, comprising: receiving a sample; selecting a target locationwithin the sample that distinguishes a target material from an innocuousmaterial; interrogating the selected target material, with a Ramanlaser, thereby producing a Raman spectrum; determining whether theinterrogated target material is suspected of being a threat material bycomparing an amplitude of a first spectral region in the Raman spectrum,to a first predetermined threshold; performing a verification, only whenthe determination indicates that the interrogated target material issuspected of being the threat material, by comparing a secondpredetermined threshold against an amplitude of a second spectral regionin the Raman spectrum measured during the interrogation, where thesecond spectral region is different from the first spectral region; andactivating an indicator if the verification indicates that theinterrogated target material is the threat material.
 2. The method ofclaim 1 further comprising: selecting a first spectral region to benarrow region that is sufficiently small to capture a single feature;wherein: interrogating the selected target material, with a Raman laser,thereby producing a Raman spectrum comprises: considering only the firstspectral region when determining whether the interrogated targetmaterial is suspected of being a threat material.
 3. The method of claim1 further comprising predetermining that the threat material is anitrate.
 4. The method of claim 3, wherein: interrogating the selectedtarget material, with a Raman laser further comprises: interrogating atleast a portion of the Raman spectrum in the first spectral region,which is set to a wave number shift around 1050 cm⁻¹.
 5. The method ofclaim 4, wherein: determining whether the interrogated target materialis suspected of being a threat material by comparing an amplitude of afirst spectral region in the Raman spectrum, to a first predeterminedthreshold comprises: comparing the amplitude of the measured portion ofthe Raman spectrum at approximately 1050 cm⁻¹ to the predeterminedthreshold, where the predetermined threshold is set to a valuecorresponding to a feature in the first spectral range that isindicative of a nitrate.
 6. The method of claim 5, wherein: performing averification, only when the determination indicates that theinterrogated target material is suspected of being the threat materialcomprises: interrogating at least a portion of the Raman spectrummeasured in the second spectral region, which is set to a wave numbershift around 3225 cm⁻¹; and comparing a second predetermined thresholdagainst an amplitude of a second spectral region in the Raman spectrummeasured during the interrogation, which where the second spectralregion is different from the first spectral region comprises:determining if the sample includes ammonium nitrate by comparing theamplitude of the measured portion of the Raman spectrum at approximately3225 cm⁻¹ to the predetermined threshold, where the second threshold isset to a value corresponding to a feature in the second spectral rangeindicative of ammonium nitrate.
 7. The method of claim 5, wherein:performing a verification, only when the determination indicates thatthe interrogated target material is suspected of being the threatmaterial comprises: interrogating at least a portion of the Ramanspectrum measured in the second spectral region, which is set to a wavenumber shift around 550 cm⁻¹; and comparing a second predeterminedthreshold against an amplitude of a second spectral region in the Ramanspectrum measured during the interrogation, which where the secondspectral region is different from the first spectral region comprises:determining if the sample includes urea nitrate by comparing theamplitude of the measured portion of the Raman spectrum at approximately550 cm⁻¹ to the predetermined threshold, where the second threshold isset to a value corresponding to a feature in the second spectral rangeindicative of urea nitrate.
 8. The method of claim 1, wherein:interrogating the selected target material, with a Raman laser, therebyproducing a Raman spectrum, comprises: using interferometricspectroscopy to interrogate at least a portion of the selected targetmaterial to produce a spectrum of the portion of the selected targetmaterial.
 9. The method of claim 1, wherein: interrogating the selectedtarget material, with a Raman laser, thereby producing a Raman spectrum,comprises: interrogating at least a portion of the sample itselfindependently of reacted material.
 10. The method of claim 1 furthercomprising detecting crystalline phases of the sample to determine aprocess of how the sample was created.
 11. The method of claim 1,wherein receiving a sample further comprises receiving the sample onto asample substrate in an open environment.
 12. The method of claim 1,wherein receiving a sample further comprises drawing in a fluid stream,which is impacted onto a sample substrate to create the sample.
 13. Themethod of claim 12, wherein receiving a sample further comprises atleast one of using a pre-impactor to filter particulates in the fluidstream to a generally predetermined size, and impacting the fluid streamonto a gold sample substrate to create the sample.
 14. The method ofclaim 1, wherein: selecting a target location within the sample thatdistinguishes a target material from an innocuous material, comprises:using a fluorescent device to select a target location by identifying afluorescing region of the sample.
 15. The method of claim 1 furthercomprising: outputting an indication of the source of an explosive ifthreat material indicative of the explosive is detected.
 16. The methodof claim 15, wherein outputting an indication of the source of anexplosive comprises determining at least one of the process andmaterials used to make the explosive and outputting determinationresults.
 17. The method of claim 1, wherein receiving a sample comprisesreceiving the sample without perturbing the native state of an explosivebeing sampled.
 18. A system for detecting threat materials used inexplosives, comprising: a sample collector that collects a sample; asample stage that receives the sample from the sample collector; aninterrogation station that includes a Raman laser source; and aprocessor coupled to memory, where the processor is programmed tointeract with the interrogation station to interrogate the sample andselect a target location within the sample that distinguishes a targetmaterial from an innocuous material; wherein the processor is furtherprogrammed to interact with the interrogation station to: interrogate,with the Raman laser source, the target material, thereby producing aRaman spectrum; determine whether the interrogated target material issuspected of being a threat material by comparing an amplitude of afirst spectral region in the Raman spectrum, to a first predeterminedthreshold; perform a verification, only when the determination indicatesthat the interrogated target material is suspected of being threatmaterial, by comparing a second predetermined threshold against anamplitude of a second spectral region in the Raman spectrum measuredduring the interrogation, where the second spectral region is differentfrom the first spectral region; and activate an indicator if theverification indicates that the interrogated target material is thethreat material.